• DocumentCode
    77718
  • Title

    Efficient Duplication Free and Minimal Keyword Search in Graphs

  • Author

    Kargar, Mehdi ; Aijun An ; Xiaohui Yu

  • Author_Institution
    Dept. of Comput. Sci. & Eng., York Univ., Toronto, ON, Canada
  • Volume
    26
  • Issue
    7
  • fYear
    2014
  • fDate
    Jul-14
  • Firstpage
    1657
  • Lastpage
    1669
  • Abstract
    Keyword search over a graph searches for a subgraph that contains a set of query keywords. A problem with most existing keyword search methods is that they may produce duplicate answers that contain the same set of content nodes (i.e., nodes containing a query keyword) although these nodes may be connected differently in different answers. Thus, users may be presented with many similar answers with trivial differences. In addition, some of the nodes in an answer may contain query keywords that are all covered by other nodes in the answer. Removing these nodes does not change the coverage of the answer but can make the answer more compact. The answers in which each content node contains at least one unique query keyword are called minimal answers in this paper. We define the problem of finding duplication-free and minimal answers, and propose algorithms for finding such answers efficiently. Extensive performance studies using two large real data sets confirm the efficiency and effectiveness of the proposed methods.
  • Keywords
    graph theory; query processing; content node; duplication free; graph search; minimal answers; minimal keyword search; query keywords; subgraph; Algorithm design and analysis; Approximation algorithms; Delays; Heuristic algorithms; Keyword search; Polynomials; Steiner trees; Algorithms; Algorithms for data and knowledge management; Computing Methodologies; Database Applications; Database Management; Information Technology and Systems; Interactive data exploration and discovery; Keyword search; Symbolic and algebraic manipulation; approximation algorithm; graph data; polynomial delay;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/TKDE.2013.85
  • Filename
    6520851